Abstract

In order to further reduce the impact of climate fluctuations on the typical meteorological year (TMY) database, this paper introduces an ensemble empirical model decomposition method to extract the periodic fluctuation and random fluctuation data from outdoor climate data separately, and to construct a comprehensive description parameter that eliminates the influence of random fluctuation data. An innovative TMY based on the comprehensive description parameter was developed in six selected cities of different climate zones in China. Compared with the existing Chinese TMY development method and outdoor design parameters, it is found that the typical meteorological months (TMMs) of each city and the outdoor design parameters from the improved TMY database have changed to a certain extent. Through the correlation analysis between improved TMY database and the cumulative long-average meteorological data, it reveals that the improved TMY can better describe the local average climatic characteristics. Finally, this paper discusses the impact of the improved TMY on the building heat loss index and outdoor thermal comfort in different building shapes. The results demonstrate that the energy demand and outdoor thermal comfort analysis based on the improved TMY are closer to long-term averaged outdoor climate, and the calculation deviations compared with conventional method are reduced by 1.18%–21.08% and 53.42%–76.82% respectively. This research will refine outdoor climate data for building design and analysis.

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